lucene4s

KO | EN

gitlite — search

#ai #nlp #pytorch #video #data-science #open-source #python #reactjs #database #ai-agent

(★ 55)

Light-weight convenience wrapper around Lucene to simplify complex tasks and add Scala sugar.

파일 탐색기

ZIP 다운로드

- - scala-steward.yml
- build.properties
- plugins.sbt
.gitignore
.travis.yml
build.sbt
LICENSE
publish.sh
README.md

# CDN으로 사용하기

jsDelivr

jsDelivr는 공개 GitHub 리포지토리를 별도 설정 없이 CDN으로 즉시 서빙합니다. 버전과 파일을 고르면 웹페이지에 바로 붙일 수 있는 링크와 예시 코드가 만들어집니다.

버전

파일

링크

예시

# 프로젝트 배지

Build Status 바로가기
Stories in Ready 바로가기
Gitter 바로가기
Maven Central 바로가기

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

Light-weight convenience wrapper around Lucene to simplify complex tasks and add Scala sugar.

## Setup

lucene4s is published to Sonatype OSS and Maven Central currently supporting Scala 2.11, 2.12, 2.13, and 3.0.

Configuring the dependency in SBT simply requires:

```
libraryDependencies += "com.outr" %% "lucene4s" % "1.11.1"
```

## Using

### Imports

You may find yourself needing other imports depending on what you're doing, but the majority of functionality can be
achieved simply importing `com.outr.lucene4s._`:

```scala
import com.outr.lucene4s._
```

### Creating a Lucene Instance

`Lucene` is the object utilized for doing anything with Lucene, so you first need to instantiate it:

```scala
val directory = Paths.get("index")
val lucene = new DirectLucene(Nil, directory = Option(directory))
```

NOTE: If you leave `directory` blank or set it to None (the default) it will use an in-memory index.

### Creating Fields

For type-safety and convenience we can create the fields we'll be using in the document ahead of time:

```scala
val name = lucene.create.field[String]("name")
val address = lucene.create.field[String]("address")
```

### Inserting Documents

Inserting is quite easy using the document builder:

```scala
lucene.doc().fields(name("John Doe"), address("123 Somewhere Rd.")).index()
lucene.doc().fields(name("Jane Doe"), address("123 Somewhere Rd.")).index()
```

### Querying Documents

Querying documents is just as easy with the query builder:

```scala
val paged = lucene.query().sort(Sort(name)).search()
paged.results.foreach { searchResult =>
  println(s"Name: ${searchResult(name)}, Address: ${searchResult(address)}")
}
```

This will return a `PagedResults` instance with the page size set to the `limit`. There are convenience methods for
navigating the pagination and accessing the results.

The above code will output:

```
Name: John Doe, Address: 123 Somewhere Rd.
Name: Jane Doe, Address: 123 Somewhere Rd.
```

### Highlighting Results

Though querying is nice, we may want to stylize the output to show the matched results. This is pretty simple:

```scala
val paged = lucene.query().sort(Sort(name)).filter(fuzzy(name("jhn"))).highlight().search()
paged.results.foreach { searchResult =>
  val highlighting = searchResult.highlighting(name).head
  println(s"Fragment: ${highlighting.fragment}, Word: ${highlighting.word}")
}
```

The above code will output:

```
Fragment: <em>John</em> Doe, Word: John
Fragment: <em>Jane</em> Doe, Word: Jane
```

### Faceted Searching

See https://github.com/outr/lucene4s/blob/master/implementation/src/test/scala/tests/FacetsSpec.scala

### Full-Text Searching

In lucene4s the `Lucene` instance holds a `fullText` `Field` that contains a concatenation of all the fields that
are configured as `fullTextSearchable`.  This defaults to `Lucene.defaultFullTextSearchable` which defaults to false.

The `fullText` field is the default field used for searches if it's not specified in the `SearchTerm`. Let's see an example:

```
val paged = lucene.query().filter(wildcard("doe*")).search()
paged.total should be(4)
paged.results(0)(firstName) should be("John")
paged.results(1)(firstName) should be("Jane")
paged.results(2)(firstName) should be("Baby")
paged.results(3)(firstName) should be("James")
```

For a complete example, see: https://github.com/outr/lucene4s/blob/master/implementation/src/test/scala/tests/FullTextSpec.scala

### Keyword Searching

As we saw previously, the `fullText` field provides us with a concatenation of all fields configured to be `fullTextSearchable`.
In addition, if you create an instance of `KeywordIndexing` you can query against a no-duplicates index of keywords for
the `fullText` (although you can override defaults to apply keyword indexing to any field). All we have to do is create
and instance referencing the `Lucene` instance and the name (used for storage purposes):

```
val keywordIndexing = KeywordIndexing(lucene, "keywords")
val keywords = keywordIndexing.search("do*")
println("Keywords: ${keywords.results.map(_.word).mkString(", ")}")
```

The above code would output:

```
Keywords: Doe
```

For the complete example see: https://github.com/outr/lucene4s/blob/master/implementation/src/test/scala/tests/SimpleSpec.scala

### Case Class Support

lucene4s provides a powerful Macro-based system to generate two-way mappings between case classes and Lucene fields at
compile-time. This is accomplished through the use of `Searchable`.  The setup is pretty simple.

#### Setup

First we need to define a case class to model the data in the index:

```scala
case class Person(id: Int, firstName: String, lastName: String, age: Int, address: String, city: String, state: String, zip: String)
```

As you can see, this is a bare-bones case class with nothing special about it.

Next we need to define a `Searchable` trait the defines the unique identification for update and delete:

```scala
trait SearchablePerson extends Searchable[Person] {
  // This is necessary for update and delete to reference the correct document.
  override def idSearchTerms(person: Person): List[SearchTerm] = List(exact(id(person.id)))
  
  /*
    Though at compile-time all fields will be generated from the params in `Person`, for code-completion we can define
    an unimplemented method in order to properly reference the field. This will still compile without this definition,
    but most IDEs will complain.
   */
  def id: Field[Int]
}
```

As the last part of our set up we simply need to generate it from our `Lucene` instance:

```scala
val people = lucene.create.searchable[SearchablePerson]
```

#### Inserting

Now that we've configured everything inserting a person is trivial:

```scala
people.insert(Person(1, "John", "Doe", 23, "123 Somewhere Rd.", "Lalaland", "California", "12345")).index()
```

Notice that we still have to call `index()` at the end for it to actually invoke. This allows us to do more advanced
tasks like adding facets, adding non-Searchable fields, etc. before actually inserting.

#### Updating

Now lets try updating our `Person`:

```scala
people.update(Person(1, "John", "Doe", 23, "321 Nowhere St.", "Lalaland", "California", "12345")).index()
```

As you can see here, the signature is quite similar to `insert`. Internally this will utilize `idSearchTerms` as we
declared previously to apply the update. In this case that means as long as we don't change the id (1) then calls to
update will replace an existing record if one exists.

#### Querying

Querying works very much the same as in the previous examples, except we get our `QueryBuilder` from our `people`
instance:

```scala
val paged = people.query().search()
paged.entries.foreach { person =>
  println(s"Person: $person")
}
```

Note that instead of calling `paged.results` we call `paged.entries` as it represents the conversion to `Person`. We can
still use `paged.results` if we want access to the `SearchResult` like before.

#### Deleting

Deleting is just as easy as inserting and updating:

```scala
people.delete(Person(1, "John", "Doe", 23, "321 Nowhere St.", "Lalaland", "California", "12345"))
```

#### Additional Information

All `Searchable` implementations automatically define a `docType` field that is used to uniquely separate different
`Searchable` instances so you don't have to worry about multiple different instances overlapping.

For more examples see https://github.com/outr/lucene4s/blob/master/implementation/src/test/scala/tests/SearchableSpec.scala

### Geospatial Support

One of the great features of Lucene is geospatial querying and what Lucene wrapper would be complete without it?

#### Creating a Spatial Field

In order to create a stored, queryable, filterable, and sortable latitude and longitude you need only create a
`SpatialPoint` field:

```scala
val location: Field[SpatialPoint] = lucene.create.field[SpatialPoint]("location")
```

#### Sorting Nearest a Point

Most of the time it's most useful to take an existing latitude and longitude and sort your results returning the
nearest documents to that location:

```scala
val paged = lucene.query().sort(Sort.nearest(location, SpatialPoint(40.7142, -74.0119))).search()
```

#### Filtering by Distance

If you want to filter your results to only include entries within a certain range of a location:

```scala
val newYorkCity = SpatialPoint(40.7142, -74.0119)
val paged = lucene
  .query()
  .sort(Sort.nearest(location, newYorkCity))
  .filter(spatialDistance(location, newYorkCity, 50.miles))
  .search()
```

lucene4s

오너의 다른 레포

파일 탐색기

# CDN으로 사용하기

# 프로젝트 배지

Was this content helpful?

Recent Feedback

lucene4s

오너의 다른 레포

파일 탐색기

# CDN으로 사용하기

# 프로젝트 배지

Was this content helpful?

Recent Feedback

Download README